Java Quality Assurance Lead (QAL)

Job Summary

As a Java Quality Assurance Lead (QAL), you will oversee quality, consistency, and contributor performance across Java AI training projects.

This role involves reviewing AI-generated Java code, evaluating trainer and QA outputs, maintaining quality standards, and ensuring training data aligns with project requirements and client expectations.

Your work will directly contribute to improving advanced AI systems by ensuring Java training content is accurate, executable, idiomatic, secure, maintainable, and clearly explained.

Key Responsibilities

Quality Monitoring

• Spot-check Java training tasks and QA outputs
• Identify recurring quality issues and performance gaps
• Provide actionable written feedback and escalate critical concerns

Code Review

• Review and evaluate:

  • Java applications
  • Spring Boot services
  • Backend implementations
  • Algorithm solutions
  • Debugging responses
  • Unit tests
  • Architecture explanations
  • Technical reasoning

• Assess work for:

  • Compile-time validity
  • Runtime correctness
  • Object-oriented design quality
  • API usage
  • Security
  • Performance
  • Maintainability
  • Test coverage

Trainer & QA Communication

• Communicate updates regarding:
  • Guidelines
  • Workflow changes
  • Java-specific review standards
  • Quality expectations

Contributor Support

• Answer questions involving:
  • Java syntax
  • Object-oriented design
  • Collections
  • Streams
  • Concurrency
  • Exception handling
  • Spring Boot
  • Testing
  • Security practices
  • Rubric interpretation

Activation Management

• Follow up with inactive contributors
• Track engagement and participation
• Report contributor availability concerns

Documentation & Onboarding

• Create and maintain:

  • Style guides
  • Documentation
  • FAQs
  • Examples
  • Calibration tasks
  • Onboarding materials

• Conduct onboarding and training sessions for contributors

Risk & Quality Review

• Identify and flag:
  • Non-compilable code
  • Logic errors
  • Unsafe concurrency
  • Weak object modeling
  • Poor exception handling
  • Inefficient algorithms
  • Hallucinated APIs
  • Non-production-ready recommendations

Process Improvement

• Improve QA workflows and review processes
• Identify recurring quality gaps and implement corrective actions

Required Qualifications

• Bachelor's or Master's degree in:
  • Computer Science
  • Software Engineering
  • Information Technology

or equivalent professional experience.

• Strong English communication skills

• Minimum 3 years of experience in:

  • Java development
  • Backend engineering
  • Enterprise software
  • JVM-based systems
  • Code review
  • Software QA
  • Technical mentoring

• Strong understanding of:

  • Object-Oriented Programming
  • Collections Framework
  • Generics
  • Streams
  • Lambdas
  • Exceptions
  • Concurrency
  • Annotations
  • JVM behavior
  • Memory management
  • Modules and packages
  • Modern Java features

• Ability to identify:

  • Logic errors
  • Poor exception handling
  • Unsafe concurrency
  • Inefficient algorithms
  • Non-compilable code
  • Hallucinated APIs

Preferred Qualifications

• Experience with:

  • Spring Boot
  • Maven
  • Gradle
  • JUnit
  • Mockito
  • Hibernate
  • JPA
  • JDBC
  • REST APIs

• Familiarity with:

  • Docker
  • GitHub
  • CI/CD systems
  • Logging frameworks
  • Profiling tools
  • IntelliJ IDEA
  • Eclipse

• Experience leading:

  • Engineers
  • Trainers
  • Reviewers
  • QA teams
  • Remote contributors

• Experience with:

  • AI training
  • Data annotation
  • LLM evaluation
  • Rubric-based code review

Why Join

• Help improve leading AI systems through technical quality assurance
• Flexible remote schedule
• Weekly payments
• Referral rewards and community incentives
• Access to future opportunities through SME Careers' expert network

Selection Process

1. AI Interview
2. Domain-Specific Assessment
3. Recruiter Interview

Important Note

There is currently no active project for this role. Qualified candidates will be added to the expert network and contacted when relevant opportunities become available.